Praveen Bhadada

12/19/2016

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Digital transformation in 2017: three must-haves for success from the partner of digital transformation at Zinnov

Together with our partners and industry experts, we continue to explore the most important and anticipated digital trends to come in 2017, from machine learning to the workplace of the future. The following is an excerpt from our recent interview with Praveen Bhadada, Partner and Global Head for Digital Transformation practice of the renowned consulting firm Zinnov.

How has the trend of digital transformation changed in recent years? What are the key components for success in this journey?

Once considered a business expense, digital transformation is now increasingly recognized by enterprises as a lever to drive both revenue uptake and cost efficiency, thereby becoming a cornerstone for exponential business impact. Our estimates show that more than 90% of Fortune 500 enterprises today are already implementing (or looking to implement) advanced digital use cases, such as advanced analytics, machine learning and IoT. We project the enterprise digital transformation to be a $136 billion market by 2020, growing at a 36% compound annual growth rate (CAGR) from the current $40 billion.

Though enterprises today realize that digital transformation is critical for success, we still see them struggling in their digital transformation journey. Enterprises need to focus on three components in their digital transformation. First comes data readiness, which forms the foundation. Digital talent is another key ingredient, which includes both training the existing talent and hiring new talent with advanced skill sets, such as machine learning. Finally, the mandate for digital transformation should come from the top down, with the CEO acting as the propeller for a common vision for the entire organization. These three are the absolute must-haves for any business starting on its digital transformation journey.

What is the ultimate goal of digital transformation?

Enhancing customer engagement and experience forms the core of digital transformation. In fact, Zinnov estimates that more than 40% of spending on digital transformation today is actually on customer targeting and engagement use cases, which includes providing more personalization, targeted promotions and omnichannel experiences to customers.

Leading retail banks are leveraging digital transformation scenarios to get a 360-degree view of customers so they can predict churn and increase retention, enhance customer segmentation for personalized marketing, and provide robo-advisors for more accuracy and speed of service provisioning. Similarly, top retailers are using advanced analytics and machine learning to provide more relevant and personalized recommendations to customers, beacon technology to provide real-time offers, and phygital omnichannel experience to help customers operate seamlessly in both physical and digital media. Lowe’s Holoroom app, Amazon Dash Button and the Home Depot mobile app are all examples in this domain.

How have data visualization tools contributed to the digital landscape?

The advent of technology has led to an explosion of data, with almost 2.5 quintillion bytes of data created daily. Though enterprises can now generate massive amounts of data, the real value lies in the ability to leverage that data and shift to actionable insights and decision support. This is where data visualization tools come into the picture.

Data visualization tools provide a highly intuitive and interactive interface that caters to a wide audience—from the tech-savvy IT professional to the average user. While most data visualization tools focus on automating the visualization of big data, we predict that these tools will eventually aim to automate the interpretation of data, provide more interactive visualizations and even automate storytelling to a certain extent.

How have companies like Uber and Airbnb achieved such incredible growth through their cloud-based platforms?

We spoke about customer experience earlier. What innovative companies like Uber and Airbnb have done is provide a cloud-based, highly intuitive and easy-to-use platform. Besides enhancing the customer experience, they have also tapped into a previously unrealized resource of suppliers (and even customers to some extent through a sharing economy model). These born-in-the-digital platforms provide a frictionless user experience that facilitates seamless interactions between the buyers and suppliers. The buyers now have more options and the ease of purchasing at the click of a button, and the sellers gain access to more buyers without the customer acquisition costs. This leads to a win-win situation for all.

What kinds of applications of machine learning do you expect to see?

Machine learning is already generating immense interest among enterprises, with more than 80% of the Fortune 500 enterprises across top industries—such as banking, financial services and insurance, retail, manufacturing, travel and healthcare—already implementing machine learning–related use cases. While retailers such as Walmart are leveraging machine learning–based search engines to provide more precise product recommendations to online shoppers, hospitals such as Cleveland Clinic are using machine learning to help doctors understand and diagnose complex medical conditions.

Machine learning not only allows enterprises to implement existing use cases with more efficiency and accuracy, it has also made it possible to tackle new challenges. For instance, enterprises can explore how to analyze customer feedback using emotion analytics without even asking the customer, or help patients with paralysis perform simple tasks using a cognitively controlled robotic arm. These net new use cases would be powered by machine learning and are set to become the new normal over the next couple of years.

What is your take on application program interfaces (APIs) with respect to digital transformation?

APIs are very interesting because they allow enterprises to open themselves to benefits such as enhanced reach, revenue generation and innovation. Twitter and Facebook are classic examples of companies that opened their APIs to third-party developers to create a richer and broader range of value-added products, thereby increasing the functionality, innovativeness, scope and reach of their platforms. Similarly, companies like eBay and PayPal have leveraged APIs, both on the buy side and sell side, and witnessed manifold growth in their number of transactions.

APIs also provide a cost-effective way for an enterprise to scale their business effectively in many directions and tap into a larger partner ecosystem. Works with Nest is a unique program from Nest that uses API technology to build a self-sustaining “smart home” marketplace by partnering with the likes of LG Appliances, Whirlpool, Philips Hue lights, and more.

What roadblocks do organizations usually face in their move to digital?

Digital transformation is about people first and then technology. In fact, the success of digital transformation depends upon the degree to which people are empowered to embrace the change for growth and innovation—not merely on the scale of technology investments. A number of surveys have indicated that lack of agility is the biggest roadblock for digital transformation, as traditional and hierarchical structures are not suited to manage the ever-changing business environment.

We already see examples of firms incorporating digital agility into their culture. The 3M Company, for instance, requires employees to spend 15% of their time on developing new products not aligned with their routine work. GE is another example, which follows the FastWorks methodology where small teams act like lean start-ups and crowdsource innovative ideas. New training techniques can bring great innovation, such as companies like Procter & Gamble and Google that swap employees to acquire critical missing skills. We anticipate similar trends gaining prominence over the next couple of years.